Evidence of unique genotypes of Beak and feather disease virus in Southern Africa

Psittacine beak and feather disease (PBFD), caused by Beak and feather disease virus (BFDV), is the most significant infectious disease in psittacines. PBFD is thought to have originated in Australia but is now found worldwide; in Africa, it threatens the survival of the indigenous endangered Cape parrot and the vulnerable black-cheeked lovebird. We investigated the genetic diversity of putative BFDVs from southern Africa. Feathers and heparinized blood samples were collected from 27 birds representing 9 psittacine species, all showing clinical signs of PBFD. DNA extracted from these samples was used for PCR amplification of the putative BFDV coat protein (CP) gene. The nucleotide sequences of the CP genes of 19 unique BFDV isolates were determined and compared with the 24 previously described sequences of BFDV isolates from Australasia and America. Phylogenetic analysis revealed eight BFDV lineages, with the southern African isolates representing at least three distinctly unique genotypes; 10 complete genome sequences were determined, representing at least one of every distinct lineage. The nucleotide diversity of the southern African isolates was calculated to be 6.4% and is comparable to that found in Australia and New Zealand. BFDVs in southern Africa have, however, diverged substantially from viruses found in other parts of the world, as the average distance between the southern African isolates and BFDV isolates from Australia ranged from 8.3 to 10.8%. In addition to point mutations, recombination was found to contribute substantially to the level of genetic variation among BFDVs, with evidence of recombination in all but one of the genomes analyzed.

The capsid protein of beak and feather disease virus binds to the viral DNA and is responsible for transporting the replication-associated protein into the nucleus

Circoviruses lack an autonomous DNA polymerase and are dependent on the replication machinery of the host cell for de novo DNA synthesis. Accordingly, the viral DNA needs to cross both the plasma membrane and the nuclear envelope before replication can occur. Here we report on the subcellular distribution of the beak and feather disease virus (BFDV) capsid protein (CP) and replication-associated protein (Rep) expressed via recombinant baculoviruses in an insect cell system and test the hypothesis that the CP is responsible for transporting the viral genome, as well as Rep, across the nuclear envelope. The intracellular localization of the BFDV CP was found to be directed by three partially overlapping bipartite nuclear localization signals (NLSs) situated between residues 16 and 56 at the N terminus of the protein. Moreover, a DNA binding region was also mapped to the N terminus of the protein and falls within the region containing the three putative NLSs. The ability of CP to bind DNA, coupled with the karyophilic nature of this protein, strongly suggests that it may be responsible for nuclear targeting of the viral genome. Interestingly, whereas Rep expressed on its own in insect cells is restricted to the cytoplasm, coexpression with CP alters the subcellular localization of Rep to the nucleus, strongly suggesting that an interaction with CP facilitates movement of Rep into the nucleus. Copyright © 2006, American Society for Microbiology. All Rights Reserved.

A unique isolate of beak and feather disease virus isolated from budgerigars (Melopsittacus undulatus) in South Africa

Beak and feather disease virus (BFDV), the causative agent of psittacine beak and feather disease (PBFD) infects psittaciformes worldwide. We provide an annotated sequence record of three full-length unique genomes of BFDV isolates from budgerigars (Melopsittacus undulatus) from a breeding farm in South Africa. The isolates share >99% nucleotide sequence identity with each other and ~96% nucleotide sequence identity to two recent isolates (Melopsittacus undulatus) from Thailand but only between 91. 6 and 86. 6% identity with all other full-length BFDV sequences. Maximum-likelihood analysis and recombination analysis suggest that the South African budgerigar BFDV isolates are unique to budgerigars, are non-recombinant in origin, and represent a new genotype of BFDV. © 2010 Springer-Verlag.

Global genetic diversity and geographical and host-species distribution of beak and feather disease virus isolates

Psittacine beak and feather disease (PBFD) has a broad host range and is widespread in wild and captive psittacine populations in Asia, Africa, the Americas, Europe and Australasia. Beak and feather disease circovirus (BFDV) is the causative agent. BFDV has an ~2 kb single stranded circular DNA genome encoding just two proteins (Rep and CP). In this study we provide support for demarcation of BFDV strains by phylogenetic analysis of 65 complete genomes from databases and 22 new BFDV sequences isolated from infected psittacines in South Africa. We propose 94% genome-wide sequence identity as a strain demarcation threshold, with isolates sharing > 94% identity belonging to the same strain, and strain subtypes sharing> 98% identity. Currently, BFDV diversity falls within 14 strains, with five highly divergent isolates from budgerigars probably representing a new species of circovirus with three strains (budgerigar circovirus; BCV-A, -B and -C). The geographical distribution of BFDV and BCV strains is strongly linked to the international trade in exotic birds; strains with more than one host are generally located in the same geographical area. Lastly, we examined BFDV and BCV sequences for evidence of recombination, and determined that recombination had occurred in most BFDV and BCV strains. We established that there were two globally significant recombination hotspots in the viral genome: the first is along the entire intergenic region and the second is in the C-terminal portion of the CP ORF. The implications of our results for the taxonomy and classification of circoviruses are discussed. © 2011 SGM.

Complete genome sequence of Colocasia bobone disease-associated virus, a putative cytorhabdovirus infecting taro

We report the first genome sequence of a Colocasia bobone disease-associated virus (CBDaV) derived from bobone-affected taro [Colocasia esculenta L. Schott] from Solomon Islands. The negative-strand RNA genome is 12,193 nt long, with six major open reading frames (ORFs) with the arrangement 3′-N-P-P3-M-G-L-5′. Typical of all rhabdoviruses, the 3′ leader and 5′ trailer sequences show complementarity to each other. Phylogenetic analysis indicated that CBDaV is a member of the genus Cytorhabdovirus, supporting previous reports of virus particles within the cytoplasm of bobone-infected taro cells. The availability of the CBDaV genome sequence now makes it possible to assess the role of this virus in bobone, and possibly alomae disease of taro and confirm that this sequence is that of Colocasia bobone disease virus (CBDV).

RNA interference-inducing hairpin RNAs in plants act through the viral defence pathway

RNA interference (RNAi) is widely used to silence genes in plants and animals. It operates through the degradation of target mRNA by endonuclease complexes guided by approximately 21 nucleotide (nt) short interfering RNAs (siRNAs). A similar process regulates the expression of some developmental genes through approximately 21 nt microRNAs. Plants have four types of Dicer-like (DCL) enzyme, each producing small RNAs with different functions. Here, we show that DCL2, DCL3 and DCL4 in Arabidopsis process both replicating viral RNAs and RNAi-inducing hairpin RNAs (hpRNAs) into 22-, 24- and 21 nt siRNAs, respectively, and that loss of both DCL2 and DCL4 activities is required to negate RNAi and to release the plant's repression of viral replication. We also show that hpRNAs, similar to viral infection, can engender long-distance silencing signals and that hpRNA-induced silencing is suppressed by the expression of a virus-derived suppressor protein. These findings indicate that hpRNA-mediated RNAi in plants operates through the viral defence pathway.

Weather variability, tides, and Barmah Forest Virus Disease in the Gladstone region, Australia

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.

Estimation on disease burden related to hepatitis B virus infection in Shandong province of China [山东省乙型肝炎病毒感染所致相关疾病的疾病负担研究]

Objective: To comprehensively measure the burden of hepatitis B, liver cirrhosis and liver cancer in Shandong province, using disability-adjusted life years (DALYs) to estimate the disease burden attribute to hepatitis B virus (HBV)infection. Methods: Based on the mortality data of hepatitis B, liver cirrhosis and liver cancer derived from the third National Sampling Retrospective Survey for Causes of Death during 2004 and 2005, the incidence data of hepatitis B and the prevalence and the disability weights of liver cancer gained from the Shandong Cancer Prevalence Sampling Survey in 2007, we calculated the years of life lost (YLLs), years lived with disability (YLDs) and DALYs of three diseases following the procedures developed for the global burden of disease (GBD) study to ensure the comparability. Results: The total burden for hepatitis B, liver cirrhosis and liver cancer were 211 616 (39 377 YLLs and 172 239 YLDs), 16 783 (13 497 YLLs and 3286 YLDs) and 247 795 (240 236 YLLs and 7559 YLDs) DALYs in 2005 respectively, and men were 2.19, 2.36 and 3.16 times as that for women, respectively in Shandong province. The burden for hepatitis B was mainly because of disability (81.39%). However, most burden on liver cirrhosis and liver cancer were due to premature death (80.42% and 96.95%). The burden of each patient related to hepatitis B, liver cirrhosis and liver cancer were 4.8, 13.73 and 11.11 respectively. Conclusion: Hepatitis B, liver cirrhosis and liver cancer caused considerable burden to the people living in Shandong province, indicating that the control of hepatitis B virus infection would bring huge potential benefits.

Spatial and temporal clusters of Barmah Forest virus disease in Queensland, Australia

Objective To identify the spatial and temporal clusters of Barmah Forest virus (BFV) disease in Queensland in Australia, using geographical information systems (GIS) and spatial scan statistic (SaTScan). Methods We obtained BFV disease cases, population and statistical local areas boundary data from Queensland Health and Australian Bureau of Statistics respectively during 1992-2008 for Queensland. A retrospective Poisson-based analysis using SaTScan software and method was conducted in order to identify both purely spatial and space-time BFV disease high-rate clusters. A spatial cluster size of a proportion of the population and a 200km circle radius and varying time windows from 1 month to 12 months were chosen (for the space-time analysis). Results The spatial scan statistic detected a most likely significant purely spatial cluster (including 23 SLAs) and a most likely significant space-time cluster (including 24 SLAs) in approximately the same location. Significant secondary clusters were also identified from both the analyses in several locations. Conclusions This study provides evidence of the existence of statistically significant BFV disease clusters in Queensland, Australia. The study also demonstrated the relevance and applicability of SaTScan in analysing on-going surveillance data to identify clusters to facilitate the development of effective BFV disease prevention and control strategies in Queensland, Australia.

Socio-environmental variability and Barmah Forest virus disease transmission : a review of epidemiological evidence and future prospects

Barmah Forest Virus (BFV) disease is the most rapidly emerging mosquito-borne disease in Australia. BFV transmission depends on factors such as climate, virus, vector and the human population. However, the impact of climatic and social factors on BFV remains to be determined. This paper provided an overview of current research and discusses the future research directions on the BFV transmission. These research findings could be regarded as an impetus towards BFV prevention and control strategies.

Spatio-temporal patterns of Barmah Forest virus disease in Queensland, Australia

Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland.

Spatial and temporal analysis of Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

Wetlands, climate zones and Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is the second most common mosquito-borne disease in Australia, but the linkages of the wetlands and climate zones with BFV transmission remain unclear. We aimed to examine the relationship between the wetlands, climate zones and BFV risk in Queensland, Australia. Data on the wetlands, climate zones, population and BFV cases for the period 1992 to 2008 were obtained from relevant government agencies. BFV risk was grouped as low-, medium- and high-level based on BFV incidence percentiles. The buffer zones around each BFV case were made using 1, 5, 10, 15, 20, 25 and 50 km distances. We performed a discriminant analysis to determine the differences between wetland classes and BFV risk within each climate zone. The discriminant analyses show that saline 1, riverine and saline tidal influence were the most significant contributors to BFV risk in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. These models had classification accuracies of 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV risk varies with wetland class and climate zone. The discriminant analysis is a useful tool to quantify the links between wetlands, climate zones and BFV risk.